• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.4
• /
• pp.330-336
• /
• 2005

An intelligent control method is proposed for control of rigid robot manipulators which achieves exponential tracking of repetitive robot trajectory under uncertain operating conditions such as parameter uncertainty and unknown deterministic disturbance. In the learning controller, exponentially stable learning algorithms are combined with stabilizing computed error feedforward and feedback inputs. It is shown that all the error signals in the learning system are bounded and the repetitive robot motion converges to the desired one exponentially fast with guaranteed convergence rate. An engineering workstation based control system is built to verify the effectiveness of the proposed control scheme.

• Proceedings of the IEEK Conference
• /
• 2001.06e
• /
• pp.143-146
• /
• 2001

Servomotors, especially linear brushless servomotors have numerous advantages over ball screws, timing belts, rack/pinion drives and friction drives compared wi th rotary servomotors This paper proposes an linear regression method as the estimated ion of unknown parameters from the linear brushless DC motor The estimated parameters are used to tune the gain of controller. In order to agree with this purpose, Digital Signal Processor (TMS320F240), developed for implementation of the motor control, is adopted in this study. The processor playing an important role in controller has A/D converters, PWM generators, riched I/O ports internally.

• East Asian mathematical journal
• /
• v.32 no.1
• /
• pp.139-152
• /
• 2016

Inflammatory Bowel Disease(IBD) is chronic, relapsing, immune mediated disorder. The exact cause of IBD is still unknown. The immune system is known to play important role in the dynamics of IBD. We focus on relation between T cells and cytokines in immune system that leads to IBD. In this paper, we propose a mathematical model describing IBD under considering immune mediated disorder by using ordinary differential equations. The existence and stability of the model are established, where an applicable basin of attraction are calculated and examined. Some numerical simulations are presented to verify the proposed results and as changing parameter values given by sensitivity analysis, we show how to change dynamic behaviors of the model.

• Communications for Statistical Applications and Methods
• /
• v.13 no.2
• /
• pp.205-217
• /
• 2006

In this paper, we consider the problem of testing for a change of the parameter function ${\theta}(t)$ that may have a discontinuity at some unknown point ${\tau}$. We introduce a varying-h moving estimate to test the null hypothesis that ${\theta}(t)$ is continuous against the alternative that ${\theta}({\tau}-){\neq}{\theta}({\tau}+)$. Simulation results are provided for illustration.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.38 no.11
• /
• pp.905-912
• /
• 1989

An adaptive control scheme is presented for uncertain systems whose uncertainties are upper-bounded by a linear combination of unknown constants and known continuous functions. The state of the closed-loop system is proven to be ultimately bounded. The proposed method modifies the method of Corless and Leitmann in the following two respects. First, the linear region of the saturation function in controller is fixed. Second, the intergration from in parameter estimator is replaced by a low pass filter form. These modifications prevent performance degradation and destabilization of the control system more effectively. The norm of the system states can be made sufficiently small by an appropriate choice of design parameters in the control law. The applicability of the proposed scheme is demonstrated in the position control of a simple pendulum via simulation.

• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2046-2048
• /
• 2003

In this paper, a neural disturbance observer(NDO) is developed and its application to the control of a nonlinear system with the internal and/or external disturbances is presented. To construct the NDO, a parameter tuning method is proposed and shown to be useful in adjusting the parameters of the NDO. The tuning method employes the disturbance observation error to guarantee that the NDO monitors unknown disturbances. Each of the nodes of the hidden layer in the NDO network is a radial basis function(RBF). In addition, the relationships between the suggested NDO-based control and the conventional adaptive controls reported in the previous literatures are discussed. And it is shown in a rigorous manner that the disturbance observation error converges to a region of which size can be kept arbitrarily small. Finally, an example and some computer simulation results are presented to illustrate the effectiveness and the applicability of the NDO.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.345-347
• /
• 1993

It is known that Feedback linearization has important limitations-the full state has to be measured; no robustness is guaranteed with respect to parameter uncertainty and unmodeled dynamics. In this paper, we construct a nonlinear feedback linearization controller for the system containing uncertain parameters and unknown states, in the case of EMS system with rail vibration. Performance of this controller is demonstrated by computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.6
• /
• pp.927-934
• /
• 2017

This paper is concerned with applicability of two-degree-of-freedom controllers to the recently suggested i-PID controllers, in which unknown parts of the plant are taken into account without any modeling procedure. First, i-PID controller with two-degree-of-freedom is applied to a specific model, called Anisochronic model, to confirm the usefulness of this method. Second, using the original examples of i-PID controllers, it is confirmed that performance/robustness of system are to be improved due to two-degree-of-freedom, especially when the input changes suddenly. It is seen that as the desired robustness increases the optimal value of two-degree-of-freedom parameter ${\alpha}_A$ would be negative. It is checked and verified that if this value was limited to 1 or less as is generally known, performance would be degraded.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.975-978
• /
• 2010

This paper presents a Kalman filter based modeling algorithm for autonomous robots. State of the robot systems is measured by using embedded sensors and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state space motion equation for unknown system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. We conduct real-time experiment to test our proposed modeling algorithm where velocity state of the constructed robot is used as system observation.

• Proceedings of the KIEE Conference
• /
• 1995.07a
• /
• pp.282-284
• /
• 1995

A robust nonlinear control technique for brushless DC(BLDC) motors is presented using a feedback linearizing technique. The nonlinear model of the BLDC motor is first linearized far the exactly known system by an input-output linearizing method. Then, the robust control is designed for the unknown parts of the system using the Lypunov second method. By employing the proposed control scheme, the a robust control performance against the parameter uncertainties is obtained and therefore a robust feedback linerizing control of the BLDC motor is realized. The effectiveness of the proposed control scheme is well demonstrated through the comparative simulations.